Diverse talent is critically important because different people hold different perspectives and, therefore, will approach tasks and solve problems differently. We need to diversify the talent pool in a variety of ways—not by over-simplifying demographic breakdown into skin tone, race, and ethnicity, but rather by recognizing differences in financial status and lifestyle.

Amazon has spent more than a year developing an AI program intended to automate recruiting for corporate and warehouse positions. This AI, dubbed Automated Applicant Evaluation (AAE), identifies résumés similar to those of current high-performing staff. The possibilities are exciting, but in 2018 Amazon pulled a previous AI recruiting tool because of an observed bias against women. Thankfully, Amazon learned a lot from this incident, and internal reports indicate that this new tech is less susceptible to race and gender bias.

Guarding against race or gender bias is not enough to ensure egalitarian recruiting, however. Where would non-traditional résumés fit into the AI screening process, such as veterans or those with career gaps (e.g., primary-care givers)? A 2022 survey conducted by the Society for Human Resource Management indicates that roughly 25% of organizations already use AI for recruiting. Still, it remains to be seen whether these automated recruiting tools genuinely select and screen candidates without any bias.

While automated recruiting platforms hypothetically prevent prejudicial candidate appraisal and hiring, they often fail to attain this standard. In this article, we will explore how utilizing automated recruiting tools may negatively impact an organization’s ability to recruit without discrimination.

The Impact of AI on Recruitment and DEI Efforts
Automated recruiting is limited by human knowledge and sociocultural beliefs, which inevitably creates potential bias within the tools themselves. Because we have historically excluded certain groups of people without cause, automated recruiting systems will rely on previous success metrics based on the group in power rather than the average person. If HR workers critically assess the most valuable data points, they may be able to take a truly objective view of candidates, but this standard is not yet attainable.

Another weakness of automated recruiting is its tendency to search for candidates with previous experience aligning directly with the current role, often throwing out quality applicants with transferable skills. This is also problematic when the automation tools include name and gender markers on documentation that don’t align with the previous success rate, as these markers are based on the biased hiring practices of the past.

In recent practice, companies like Google and Microsoft have eliminated degree requirements, instead prioritizing previous experience and desired skills. This has not yet been applied to automation, as it involves human-dependent data synthesis and analysis.

Why It’s Important to Prioritize DEI Best Practices
Diverse talent is critically important because different people hold different perspectives and, therefore, will approach tasks and solve problems differently. We need to diversify the talent pool in a variety of ways—not by over-simplifying demographic breakdown into skin tone, race, and ethnicity, but rather by recognizing differences in financial status and lifestyle.

People from different backgrounds will also likely have different viewpoints on community impact and involvement. By prioritizing DEI efforts, you not only bring in qualified talent that helps break the monotony of mindset and disrupts groupthink, but you expand the community outreach effort and open the door to exceptional talent opportunities. Consequently, more people that may not have previously interacted with the company or organization join your talent network. It becomes a value-driven mission rather than a profit-driven mission, which historically often lends itself to long-term success and greater reputability across different communities.

If you fail to include DEI ideology from the get-go, your competition will move faster and further due to the influx of available automated recruiting technology. People from a variety of backgrounds will have an automatic proclivity toward different technology based on need and familiarity. For example, Kodak relied too heavily on its existing norms, company culture, and organizational structure; the company has since lost market share to Instagram, a company that was willing to innovate and evolve over time. Without having a focus on diversity––in all its forms––you will lose insight into how you can keep pace with the zeitgeist, the changing nature of your target market, and how to incorporate new ideas and new perspectives.

Here are several ways how AI can be used in HR while still supporting DEI:

• Automated recruiting needs improved parameters and data sets for gender, race, and expression. To solve this problem, automation in HR needs to include a more inclusive definition of education standards, formal education, as well as apprenticeship and mentorship and how they play into the hiring process.

• Hire a team of people from a variety of backgrounds to create new recruiting technology that will help remove the pitfalls of previous data sets that no longer apply to the current market nor are beneficial to the overall structure of the business world. This will create a broader talent network by sampling a larger pool of experience.

• Create a system that doesn’t highlight missing elements (like degrees or certifications) but instead includes a variety of relevant backgrounds and skills. Removing the name bias in crawling automation helps include a greater breadth of candidates while compiling a skill thesaurus. Incorporating the various experiences applicable to the role helps to identify candidates who will approach problems creatively rather than with outdated methods.

Automation isn’t a singular solution to DEI; it’s a tool. The real work is finding out how to change organizational culture and eliminate groupthink, discrimination, and biased perspectives. This requires human input and hard decisions. The good news is that we can use automation to discover, evaluate, and hire the best talent while working to change the organization and determining the most effective automated recruiting strategy.